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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 181–190 of 2226 papers

Title	Date	Tasks	Status	Hype
Particle Flow Bayes' Rule	Feb 2, 2019	Bayesian InferenceMeta-Learning	CodeCode Available	1
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance	Nov 18, 2022	Bayesian InferenceDomain Adaptation	CodeCode Available	1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics	Jan 31, 2020	Bayesian InferencePhysical Simulations	CodeCode Available	1
Multi-marginal optimal transport and probabilistic graphical models	Jun 25, 2020	Bayesian Inference	CodeCode Available	1
Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive Models	Nov 23, 2022	Bayesian InferenceTime Series	CodeCode Available	1
Neural Variational Gradient Descent	Jul 22, 2021	Bayesian Inferenceregression	CodeCode Available	1
Understanding and Accelerating Particle-Based Variational Inference	Jul 4, 2018	Bayesian InferenceVariational Inference	CodeCode Available	1
Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces	Jun 19, 2021	Bayesian InferenceOut-of-Distribution Detection	CodeCode Available	1
Parallel Streaming Wasserstein Barycenters	May 21, 2017	Bayesian Inference	CodeCode Available	1
Pick-and-Mix Information Operators for Probabilistic ODE Solvers	Oct 20, 2021	Bayesian Inference	CodeCode Available	1

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	F-SWA	Accuracy	83.61	—	Unverified
2	F-SWAG	Accuracy	80.93	—	Unverified